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Pre-trained POS tagging models for German social media

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DataCite Commons2025-01-28 更新2025-04-17 收录
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https://heidata.uni-heidelberg.de/citation?persistentId=doi:10.11588/DATA/W3JBV4
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<p>Pre-trained POS tagging models for</p> <ol style="list-style-type: lower-alpha;"> <li>the HunPos tagger (Halácsy et al. 2007)</li> <li>the biLSTM-char-CRF tagger (Reimers & Gurevych 2017)</li> <li>Online-Flors (Yin et al. 2015).</li> </ol> <p><strong>References:</strong></p> <p>Halácsy, P., Kornai, A., and Oravecz, C. (2007). HunPos: An open source trigram tagger. In <em>Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions</em>, ACL’07, pages 209–212, Prague, Czech Republic.</p> <p>Reimers, N., and Gurevych, I. (2017). Reportingscore distributions makes a difference: Performancestudy of lstm-networks for sequence tagging. In <span style="left: 171.017px; top: 1330.24px; font-size: 14.944px; font-family: sans-serif; transform: scaleX(0.931795);">Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing</span>, EMNLP, pp. 338–348, <span style="left: 200.077px; top: 1344.41px; font-size: 14.944px; font-family: sans-serif; transform: scaleX(0.915778);">September 7–11, 2017, Copenhagen, Denmark.</span></p> <p>Yin, W., Schnabel, T. and Schütze, H. (2015). Online updating of word representations forpart-of-speech tagging. In <em>Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing</em>, EMNLP’15, pages 1329–1334. September 17-21, 2015, Lisbon, Portugal.</p>
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heiDATA
创建时间:
2020-03-26
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